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Accelerating Streamline Tracking in Groundwater Flow Modeling on GPUs
Xiaohui Ji1, Mulan Luo1, Xu-Sheng Wang2
1School of Information Engineering, China University of Geosciences, Beijing, 100083, China.
Abstract:
Streamline simulation in groundwater flow modeling is a time-consuming process when a large number of streamlines are analyzed. We develop a parallelization method on graphics processing units (GPUs) for the semi-analytical particle tracking algorithm developed by Pollock (1988). Compute Unified Device Architecture was used to implement the parallel method. Forward and backward tracking of a streamline is handled by an individual thread. A GPU includes a grid of blocks where a block handles 32 threads. We use multi-GPUs to accelerate streamline tracking in a flow model with millions of particles. The method was examined to simulate streamlines for identifying three-dimensional (3D) flow systems in a Tóthian basin. The speedup exceeds 1000 when 8 NVIDIA GPUs are used to simulate 5 million or more streamlines.
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